two-tone pseudo coloring for multiple...
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Two-Tone Pseudo Coloringfor Multiple Variables
OverviewGoal: Visualization of multivariate data
Approach: Combine advantages of● Two-Tone Pseudo Coloring (TTPC)● TableLens● Self-Organizing Maps (SOM)
Challenges:● TTPC supports only 1-D data● TTPC's efficiency decreases for high-frequency data● Improve readability of TTPC
Visual Layout and MappingTabular layout:
● Relies on the well-known TableLens approach● Larger number of data rows can be represented
Color Coding:● Makes use of TTPC to color-code each table cell● Allows for more variables to be visualized within the TableLensSOM Sorting
● Generate SOM with number of neurons and training phases estimated based on number of variables and data rows● Apply SOM to sort the data with respect to all or user-selected variables
● High frequencies in visual representation are reduced● Clusters may be identified
● Side effect: hierarchical data structure can be used to drive interface for information drill-down
TableLens, Rao & Card, 1994 Two-Tone Pseudo Coloring, Saito et al., 2005
Improve Readability● Color scale has major impact on efficiency of TTPC● Key to comprehensibility: segmentation of color scale● Simple heuristics help to generate easier interpretable color scales
Mathias John, Christian Tominski, & Heidrun SchumannUniversity of Rostock, Germany
Basic color segment computation Heuristics applied
Data with high frequencies
SOM Sorting
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